How to leverage AI and data science to make business sustainable

In this second of two articles on the role that industry can play in tackling the climate emergency, Ekimetrics’ Théo Alves da Costa and Laurent Félix detail the ways in which businesses can make the best use of AI and data science to transform industry towards sustainability.

We know that AI and data science can play a pivotal role in the process of transformation towards sustainability. As the IPCC has noted: “Digitalization can enable emission reduction, but can have adverse side effects unless appropriately governed.” This is not simple. “Appropriate governance” in the application of AI and data science on the sustainability journey requires industry to:

• Be aware that everything has an impact and so always question needs and requirements
• Put technology in its rightful place as a means to an end but not an end in itself
• Choose your battles, hit the right spot, and do so quickly
• Measure both direct and indirect impacts, and face up to responsibilities – including for what turn out to be unintended consequences

Why it’s time to … Measure – Decide – Optimize

At Ekimetrics, we use a three-step framework to help companies institute meaningful change as they evolve their business models to be a constructive part of a sustainable future.

This is distinctly different from the way that some environmental consultants – inspired by traditional, bottom-up accounting practices – have approached measuring a company’s environmental impact as an academic exercise in which every last gramme of carbon must be counted in granular detail before any action can be taken. Data science and AI turn this thinking on its head and empower business to be very much more agile and measure what matters. By mapping out the impacts and contingencies – of research and development, production and manufacture, distribution and sale, decommission and recycling – data scientists are able to build an accurate (if at first approximate) understanding of a company’s total impact. This can be done in a matter of weeks and lead to immediate, remedial action.

Having identified, say, 60% of a company’s carbon impact, our data scientists can use AI to model a further 20% – perhaps further down the supply chain or in other markets or categories – while the first 60% is being addressed. The ability for AI to process – for example – unstructured, textual data and extract qualified information using natural language processing allows businesses to fill gaps in the data record. The final 20% can be assessed using a standard, bottom-up accounting model.

Towards a new set of metrics

The Measure –Decide – Optimize approach allows organizations to get a grip on the metrics that matter. Financial performance, margin, top- and bottom-line profitability are all still important. Of course they are. But just as nations and global economists have come to fetishize Gross Domestic Product (GDP) as the one metric of overwhelming importance almost at the exclusion of anything else, so financial metrics have for too long been the sole concern of corporations, boards, and CFOs. The relentless, country-level preoccupation with GDP and GDP growth has in turn led to industry’s obsession with corporate growth. The top-down focus fuels the bottom-up fixation, with national GDP growth the product of corporate expansion.

In a new economy that looks to meet the needs of all within the means of the planet, companies will need to measure and report both differently and more broadly. Triple bottom line reporting demands that companies focus on social and environmental impact in addition to financial performance; profit, yes, but also people and planet. This means that there is an opportunity for the Chief Financial Officer to become the Chief Value Officer, or for the Chief Value Officer to become a new, standard, and senior appointment to all boards.

Triple bottom line reporting demands that companies focus on social and environmental impact in addition to financial performance; profit, yes, but also people and planet.

What is Ekimetrics doing to help companies transform their business model?

Ekimetrics consultants sit at the sweet spot of data science expertise, business strategy know-how, and a deep understanding of sustainability. Currently, we offer three data-driven products and services that put data science and AI at the heart of the engine to deliver genuine transformation.

Transition Score

This 360° platform enables companies to visualize, track, and pilot all ESG insights at a portfolio / multi-brand and multi-market level, ranking their efforts to transform their business for a sustainable future. It enables an at-a-glance understanding of how they can transition from simple ESG reporting to long-term impact. The Transition Score platform helps companies to move beyond greenwashing and assess the positive impact of a broad array of potential activities, covering carbon intensity and decarbonization, science-based pledges and targets, and sectoral trajectories. It also enables businesses to simulate the impact of future actions and commitments.

Pathways

Knowing where to go and why is critical, particularly in an area of business transformation that is both so urgent and yet so new and alien to many businesses. Pathways starts with a rapid, accurate, but not 100% perfect statistical estimation of your carbon footprint. Hybrid algorithms recommend a science-based decarbonization trajectory and action plan, incorporating net zero reduction targets to be reached in the short, medium, and long term. The platform automatically scales to address portfolios of products in different categories or markets, different financial assets, and different suppliers right across your supply chain.

ESG Platform

The latest addition to the Ekimetrics suite of data-driven sustainability tools, ESG Platform analyzes any and all unstructured data and text documents reporting on climate-related and environmental issues pertinent to and touching your business operations. Data sources ingested include: corporate and activist websites, news media, analysts’ financial reporting, and content from social media networks. This intelligence platform empowers senior management to know – with confidence – where they should invest their company’s time and resources to have the quickest and biggest impact. It also helps them to know what to avoid.

In summary

Changing business models, decarbonizing supply chains, and moving from a linear to a circular economy isn’t easy, and time is against us. We have no time to waste and action is required today to limit our impact on our increasingly fragile ecosystem – not tomorrow or three years from now. Business decision-making is often slow and considered; we don’t have time for slow and considered. Fortunately, AI and data science provide every business with both the tools and the opportunity to scope quickly where they can make the biggest dent on their own particular negative impact on the planet – and then to scale those improvements across their business and across their supply chain.

Théo Alves Da Costa is Head of AI for Sustainability & Climate at Ekimetrics (LinkedIn), and Laurent Félix is General Manager, France, & Partner at Ekimetrics (LinkedIn).

You can read here the first article in this series on how data science can drive sustainable transformation